While the automatic location and recognition at high speed of the addresses on standard letters has long been practiced (cf. for example, A. K. Jain et al.; Pattern Recognition, Vol. 25, No. 12, p. 1459 ff.; Pergamon Press Ltd., 1992) and is used in almost all post offices, this still causes some difficulty for so-called packets (e.g. DIN A4, B4) and parcels. The reason for this lies in the very large amount of data (large area) which has to be processed in the case of the corresponding objects as well as in the high data transfer speed required for the high throughput. In addition, the rational recognition of the address is made difficult by the frequently very non-uniform position of the address on the object. Rational recognition of the address is made even more difficult in the case of large letters and parcels (such as, for example, journals, catalogues or advertising material) by an often very varied multi-colored background compared with standard letters in which color information plays a rather subordinate role. Until now, therefore, such objects are sorted exclusively by hand. Recently, automatic equipment has come onto the market which recognizes addresses by using a high definition grey scale camera (cf, for example, A. K. Jain et al., "Address block location on envelopes using Gabor filters", Pattern Recognition, Vol. 25, No. 12, pp. 1459-1477, 1992 or S. N. Srihani et al., "Recognising Address Blocks on Mail Pieces", Al Magazine, Winter 1987, pp. 25-40). In this way the image of the object to be read is obtained as a grey scale image, converted to a binary image and finally processed with a so-called "textblock finder", which is capable of locating text components and of combining these into words, lines and finally "text blocks" , which are possible "candidates" for address data.
After the correct address block has been determined through a knowledge-based system or a neural network or through statistical classifiers (where, i.a., features such as length or height of the text block, the number of lines and the ratio between black and white pixels are involved), it is finally read by an OCR (optical character recognition) reader (cf., for example, S.N. Sriheri et al., "Towards developing a real time system to locate address blocks on mail pieces", Int. Il. Res. & Engng. Postal Appl., 1(1), pp. 57-65, 1989).
The recording of grey scale or color images is generally effected by passing the object to be read uninterruptedly through a light slit produced by a suitable illuminating device. In this way, the whole surface of the document is recorded by means of a grey scale camera directed at this light slit and subsequently digitized.
In the case of complex colored packets and parcels, however, the address block often cannot be found in this grey scale or binary image, because of the low data density of the address block in comparison with the large amount of other unwanted information on the object.
In order to be able to use OCR in the automatic sorting of packets and parcels it is necessary to digitize the whole surface at at least 200 dpi (dots per inch) (=8 bit grey scale values per pixel), in order to be able to resolve small letters. The resultant quantity of data and the frequently highly colored surface of a large letter or parcel make the search for the address block much more difficult.
An important criterion in evaluating the capacity of a fully automated address recognition system is the throughput (reading speed) and recognition rate. Thus improvements in recognition of just one percent lead to cumulative savings of millions. In order to extend the potential of such a system to its fullest extent, all requisite information must be recorded as soon as the camera has recorded the object and subsequently processed by methods suited to the specific recording system.
For address recognition of packets and parcels which also contain color information it therefore seemed desirable to record and evaluate this color information additionally, where the recording of the color information (at a lower resolution) can serve for the rapid and certain location of the address and the recording of grey value data (at a higher resolution) for the actual reading of the address data.
F. Ade et al., "A two-step procedure to find the destination address block on parcels, Actes des premieres journees europeennes sur les technologies postales", Proceedings, Nantes, France, 14-16 June 1993, Vol. 1, pp. 303-320, describes a two stage process for address block recognition on parcels.
For this, possible "address block candidates" are extracted in a first stage using a low resolution color image (1 pixel/mm) of the whole of one side of the parcel, from which, based on characteristic features, the actual address blocks are identified. In a second step, a high resolution (4 pixels/mm) binary image is then produced, from which the address block is then read by means of OCR.
One disadvantage of this method is the very low reading rate (ca. 5 min per parcel)
It is possible to obtain color and grey scale data at different positions on the object to be processed with two illuminating devices separated from one another. However, for this, additional illuminating devices, the corresponding adjustment, object start and end signals or even object tracking (where the distance between the two exposures is large) are generally required.
The IBM Bulletin "M.A.R.S., IBM Automatic Mail Address Recognition System", March 1995, describes such an automated address recognition system consisting of a low resolution color camera and a high resolution grey scale camera.
A further problem with the simultaneous recording of color and grey scale data resides in the fact that different light intensities are required for the two exposures as a result of the differences in resolution.
In addition, a high reading speed generally requires a high light intensity in order to illuminate adequately the lines on the object which are to be read.